An LPV modelling and fault diagnosis in wind turbine benchmark system
In order to keep away wind turbines from catastrophic conditions due to sudden breakdowns, it is important to detect faults as soon as possible. For diagnosis, a model-based approach is chosen. There are many works that use this fault detection design, but the majority of them consider this system a...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/115909 |
| Acceso en línea: | https://hdl.handle.net/2117/115909 https://dx.doi.org/10.1504/IJMIC.2017.084718 |
| Access Level: | acceso abierto |
| Palabra clave: | Fault location (Engineering) Control theory Wind turbines--Automatic control LPV modelling model-based fault diagnosis residue subspace identification wind turbine Control, Teoria de Tolerància als errors (Enginyeria) Errors de sistemes (Enginyeria) Aerogeneradors Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
| Sumario: | In order to keep away wind turbines from catastrophic conditions due to sudden breakdowns, it is important to detect faults as soon as possible. For diagnosis, a model-based approach is chosen. There are many works that use this fault detection design, but the majority of them consider this system as a linear time invariant (LTI) model. The objective of this paper is, first, to find an LPV model of the system using the subspace identification technique of linear parameter-varying (LPV). Second, we focus on fault diagnosis based on residual generation which is obtained as a comparison between the measured variable and the estimated one using this LPV model. In this work, a benchmark of a wind turbine case is proposed with six predefined faults (three sensor fault scenarios, two actuator fault scenarios and a system fault scenario). |
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